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The rapid urbanization in China has brought about serious air pollution problems, which are likely to persist for a considerable period as the urbanization process continues. In urban areas, the spatial distribution of air pollutants represented by PM 2.5 has been proved mainly affected by emission, urban landscape pattern (short as ULP), as well as meteorological conditions. However, the contributions of these factors can seriously vary with different periods of urban development. Based on multi-source data, 304 prefecture-level cities in China were chosen as study areas, and we used the Geographically and Temporally Weighted Regression (GTWR) model to quantify the relative contributions of three factors-emission, ULP, and meteorological condition-to PM 2.5 concentration variation in different periods, namely, the Slow Ascending Period (SAP, 2000-2007), the Stable High-level Period (SHP, 2007-2013), and the Rapid Decline Period (RDP, 2013-2020). During SAP, the relative contribution of emission remained low and the relative contribution of ULP decreased, while the contribution of meteorological factors to PM 2.5 concentration variation becoming the dominant factor. During SHP and RDP, the relative contribution of emission notably increased (The largest increase is 28 %), while the relative contribution of meteorological factors significantly decreased (The largest decrease is 16 %). Spatially, the key regions for air pollution control in China, such as the Beijing-Tianjin-Hebei, the Fenwei Plain, the Yangtze River Delta, and the Pearl River Delta, experienced a significantly greater decrease (The largest decrease is 39 %) in the meteorological contribution and increase in the emission contribution (The largest increase is 66 %) compared to other regions. In general, we found that 27 cities in southwest China become increasingly sensitive to meteorological conditions, while the majority of cities (277 in total), particularly in key regions, have shown a growing sensitivity to emission during the whole period. These results prove that the ability of anthropogenic influence on air quality is gradually more effective, indicating the air pollution prevention and control policies in China in recent years have achieved satisfactory results. It is worthy to notice that the PM 2.5 level in most cities is still sensitive to emissions. Therefore, strict emission reduction measures still needs to implemented in the future to further improve air quality., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2025 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Estimating PM 2.5 exposure and its health impacts in cities involves large uncertainty due to the limitations of model resolutions. Consequently, attributing the sources of PM 2.5 -related health impacts at the city level remains challenging. We characterize the health impacts associated with chronic PM 2.5 exposure and anthropogenic emissions in Shanghai using a chemical transport model (GEOS-Chem) and its adjoint. By incorporating high-resolution satellited-derived PM 2.5 estimates into the calculation, we investigate the response of PM 2.5 exposure and its related health impacts in Shanghai to changes in anthropogenic emissions from each individual region, species, sector, and month. We estimate that a 10% decrease in anthropogenic emissions throughout China avoids over 752 (506-1,044) PM 2.5 -related premature deaths in Shanghai, with changes in local emissions potentially saving 241 (161-334) lives. Ammonia (NH 3 ) emissions are identified as the marginal dominant contributor to the health impacts due to the NH 3 -limited PM 2.5 formation within the city, thus controlling NH 3 emissions at both the local and regional scales are effective at reducing the population's exposure to PM 2.5 . A negative response of the PM 2.5 exposure to local nitrogen oxides (NO x ) emission changes is detected in winter. Even so, controlling NO x emissions is still justified since the negative impacts decrease as anthropogenic emissions decline and NO x emission reductions benefit the public health on average. The anthropogenic emission changes due to Clean Air Actions helped avoid 3,132 (2,108-4,346) PM 2.5 -related premature deaths in 2019 relative to 2013, most of which are associated with emission reductions in the agricultural and industrial sectors., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2025 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Existing environmental quality indices often fail to account for the varying health impacts of different exposures and exclude socio-economic status indicators (SES)., Objectives: To develop and validate a comprehensive Environmental Quality Health Index (EQHI) that integrates multiple environmental exposures and SES to assess mortality risks across Australia., Methods: We combined all-cause, cardiovascular, and respiratory mortality data (2016-2019) from 2,180 Statistical Areas Level 2 with annual mean values of 12 environmental exposures, including PM 2.5 , ozone, temperature, humidity, normalized difference vegetation index, night light, road and building density, and socioeconomic status. Exposure-mortality relationships were estimated using a spatial age-period-cohort model, and EQHIs (scored 0-100, with higher values indicating better conditions) were constructed. Validation was performed using K-fold cross-validation and spatial regression models., Results: Validation showed strong model performance (R-squared = 83.53 %, 75.55 %, and 52.44 % for EQHI-all cause, EQHI-CVD, and EQHI-Resp). Each interquartile increase in EQHI-all cause reduced all-cause mortality risk by 10 %, with similar reductions for cardiovascular and respiratory mortality. Geographically, EQHIs were higher in south, east, and southeast coastal regions. From 2016 to 2019, SA2s with the highest EQHI (>75) decreased from 27.1 % to 21.1 %. The population weighted EQHI was highest in Hobart and lowest in Darwin., Conclusions: We established, to our knowledge, the first tool to quantify and communicate environmental health risks using three types of mortality data and 12 environmental factors. This EQHI provides a robust framework to assess environmental health risks and guide targeted interventions. Our methodology can be adapted globally to standardize risk evaluation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2025 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: Exposure to fine particulate matter (PM 2.5 ) has been linked to visual impairment. Nevertheless, evidence associating PM 2.5 constituents with visual impairment in schoolchildren is sparse., Objectives: To explore the effects of long-term exposure to PM 2.5 and its constituents on visual impairment., Methods: We conducted a large cross-sectional population-based study to recruit 59,054 schoolchildren from four cities in Guangdong province, China, and used the ChinaHighAirPollutants (CHAP) dataset to estimate 3-year average concentrations of PM 2.5 and its constituents (black carbon (BC), organic matter (OM), nitrate (NO 3 - ), sulfate (SO 4 2- ) and ammonium (NH 4 + )) based on individuals' home addresses. Visual acuity was measured with a standardized logarithmic chart, and visual impairment was defined as visual acuity below 4.9 (Snellen 5/6 equivalent) in at least one eye. We utilized generalized linear mixed models and weighted quantile sum regression to assess the association between PM 2.5 constituents and visual impairment., Results: The observed associations typically displayed a nonlinear pattern. Compared to the lowest quartile of PM 2.5 and its constituents, the fourth quartile was associated with higher odds of visual impairment in schoolchildren (e.g., the adjusted odds ratio (OR) was 1.23 (95% CI: 1.13, 1.33) for PM 2.5 , 1.53 (95% CI: 1.40, 1.67) for OM, and 1.35 (95% CI: 1.27, 1.44) for BC), respectively. Similarly, joint exposure to PM 2.5 constituents was associated with visual impairment (OR = 1.17, 95% CI: 1.13, 1.22), while BC and OM contributed more to the observed associations., Conclusions: Long-term exposure to PM 2.5 and its constituents was significantly associated with higher rates of visual impairment in schoolchildren, with combustion-related BC and OM potentially driving the observed associations., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2025. Published by Elsevier Ltd.)

Tire wear particles (TWPs) are generated with every rotation of the tire. However, obtaining TWPs under real driving conditions and revealing key factors affecting TWPs are challenging. In this study, we obtained a TWPs dataset by simulating tire wear process under real driving conditions using a tire wear simulator and custom-designed test conditions. This study shows that tire wear PM 2.5 accounts for about 65 % of PM 10 . The response relationship between TWP emissions (both PM 2.5 and PM 2.5-10 ) and factors (the radial force, the lateral force, the tangential force, speed, driving torque, tire contact area, total contour length and tire tread temperature) was obtained by machine learning (ML) method. The random forest (RF) model was developed and displayed good prediction performance with an R 2 of 0.84 and 0.78 for PM 2.5 and PM 2.5-10 on the test set, respectively. Model-related (similarity network graph) and model-unrelated (partial dependence plots and centered-individual conditional expectation plots) explainability methods were used to break the black box of ML. Model explainability results show that the feature parameters-emission response relationships for tire wear PM 2.5 and PM 2.5-10 are different. Avoiding strenuous driving behaviors (TTF < 400 N, TLF < 400 N), reducing tread temperature (T < 45℃), and minimizing the number of small tread patterns are feasible ways to reduce TWPs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: Although there is increasing evidence that environmental exposures are associated with the risk of neurodegenerative conditions, there is still limited mechanistic evidence evaluating potential mediators in human populations., Methods: UK Biobank is a large long-term study of 500,000 adults enrolled from 2006 to 2010 age 40-69 years. ICD-10 classified reports of dementia cases up to 2022 (Alzheimer's disease, vascular dementia, dementia in other classified diseases, and unspecified dementia) were identified from health record linkage. Estimates of residential air pollution, traffic noise, and greenspace exposure have been modelled. Structural brain MRI was conducted from 2014 to 2022, with brain volumes relevant to dementia identified a priori. Associations between environmental exposures, brain volumes, and dementia cases (diagnosed post-MRI) were tested using linear and logistic regression and adjusted for age, sex, household income, ethnicity, education, smoking, and area-level deprivation. Mediation of exposure-outcome associations by plausible brain volumes (those associated with both environmental exposure and dementia outcomes) were modelled using the quasi-Bayesian Monte Carlo method (N = 34,817-39,772)., Results: Small but significant mediating effects (2%-8% of relationships mediated) were observed between PM 2.5abs exposure and dementia risk by reduced total brain volume, NOx and Alzheimer's disease risk by reduced peripheral cortical grey matter, PM 2.5abs and vascular dementia risk by reduced peripheral cortical grey matter, PM 2.5abs and other dementia risk by reduced total grey matter, and PM 10 and other dementia risk by reduced total grey matter. Greenspace and noise were not associated with dementia outcomes in the subset of the cohort providing brain imaging data., Conclusions: This study adds to existing evidence of associations between environmental exposures and dementia outcomes. Our findings provide novel evidence that differences in brain volume may mediate these relationships. Future research is required to prove this mechanism and establish the other mechanisms through which exposure to air pollution might increase dementia risk., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Recent increases in nitrogen dioxide (NO 2 ) and ozone (O 3 ), two highly reactive and oxidative pollutants, have raised concerns about their potential impact on adolescent mental health. This study leveraged data from the Chinese National Survey on Students' Constitution and Health (CNSSCH) in 2019, a nationally representative cross-sectional survey of Chinese adolescents. A total of 149,697 adolescents aged 10-18 years were included in this study. NO 2 and O 3 were sourced from the ChinaHighAirPollutants dataset, and the combined oxidative potential (O X ) was subsequently calculated using the concentrations of NO 2 and O 3 . The study quantitively examined the association of NO 2 , O 3 , and O X with adolescent mental health using the Dual Factor Model of Mental Health (DFM), which was derived from a questionnaire. According to the DFM, mental health status was divided into four groups: complete mental health, vulnerable, symptomatic but content, and troubled. Greenness around schools, measured by the Normalized Difference Vegetation Index (NDVI), was examined for its potential effect modification on the association between NO 2 , O 3 , O X , and mental health. Each IQR (Interquartile Range) increase in O X was related to adverse mental health outcomes, with ORs of 1.17 (95 % CI: 1.06, 1.29) for being vulnerable, 1.20 (95 % CI: 1.12, 1.28) for being more symptomatic but content, and 1.15 (95 % CI: 1.07, 1.23) for being troubled. Similar findings emerged in relation to O 3 exposure. A positive association was observed between NO 2 exposure and being vulnerable (OR = 1.07; 95 % CI: 1.01, 1.16). Additionally, the impact of exposure to NO 2 , O 3 , and O X on mental health outcomes was significantly stronger in the low-level NDVI group compared to the high-level NDVI group (P for interaction < 0.05). The joint effects analysis revealed that adolescents exposed to high levels of air pollutants and low NDVI had the highest odds of adverse mental health outcomes. These results highlight the complex relationship between NO 2 , O 3 , O X , and mental health, with particular emphasis on the underexplored role of O X . Notably, the findings suggest that reducing pollution and increasing greenery could offer significant benefits for improving adolescent mental health., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Ozone (O 3 ) is a significant contributor to air pollution and the main constituent ofphotochemical smog that plagues China. Nitrogen dioxide (NO 2 ) is a significant air pollutant and a critical trace gas in the Earth's atmosphere. The presence of O 3 and NO 2 has detrimental effects on human health, the ecosystem, and agricultural production. Forecasting accurate ambient O 3 and NO 2 concentrations with full spatiotemporal coverage is pivotal for decision-makers to develop effective mitigation strategies and prevent harmful public exposure. Existing methods, including chemical transport models (CTMs) and time series at air monitoring sites, forecast O 3 and NO 2 concentrations either with nontrivial uncertainty or without spatiotemporally continuous coverage. In this research, we adopted a forecasting model that integrates the random forest algorithm with NASA's Goddard Earth Observing System "Composing Forecasting" (GEOS-CF) product. This approach offers spatiotemporally continuous forecasts of O 3 and NO 2 concentrations across southeastern China for up to five days in advance. Both overall validation and spatial cross-validation revealed that our forecast framework significantly surpassed the initial GEOS-CF model for all validation metrics, substantially reducing the errors in the GEOS-CF forecast data. Our model could provide accurate near-real-time O 3 and NO 2 forecasts with continuous spatiotemporal coverage., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2025 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Wind erosion from farmland is a significant contributor to atmospheric particulate matter, particularly PM 10 (atmospheric particulate matter with an aerodynamic diameter ≤ 10 μm), in regions with intensive agricultural activities such as the North China Plain (NCP). However, the specific impact of farmland dust emissions on regional air quality remains underexplored. This study integrated the Wind Erosion Prediction System (WEPS) model with the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to investigate the effect of agricultural dust emissions on PM 10 concentrations in the NCP. Results indicated that wind erosion from agricultural fields in the NCP produced approximately 33.8 × 10 5 tons of PM 10 annually. These emissions are predominantly concentrated during the winter months from October to next April, with the highest emissions occurring in Hebei, Henan, and Shandong provinces. Using scenario experiments with the WRF-Chem model, we further quantified the contribution of agricultural dust emissions to atmospheric PM 10 concentrations. The findings revealed that farmland emissions contributed approximately 13% of atmospheric PM 10 concentrations during winter months (January and December), underscoring the significant role of agricultural activities in regional air pollution. This study highlights the importance of including farmland wind erosion into chemical transport models to more accurately understand and mitigate the effects of agricultural activities on atmospheric pollution in agricultural regions worldwide., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Countries in South Asia are suffering severe PM 2.5 pollution with rapid economic development, impacting human health and the environment. Whilst much attention has been given to understanding the contribution of primary emissions, the contribution of agriculture to PM 2.5 concentrations, especially from agricultural ammonia (NH 3 ) emissions, remains less explored. Using an advanced regional atmospheric chemistry and transport modelling system (WRF-EMEP) with a new estimate of anthropogenic NH 3 emissions inputs, we estimate the influence of agricultural NH 3 emissions on surface PM 2.5 in South Asia and evaluate the health impacts and the economic losses attributable to PM 2.5 in 2018. Results show that WRF-EMEP can reproduce magnitudes and variations of PM 2.5 well, with a high annual mean PM 2.5 concentration that exceeds 120 µg/m 2 and mainly appeared in the Indo-Gangetic Plain. We estimate 2,228,000 (95 % Confidence Interval: 2,052,000-2,400,000) premature deaths and US$ 596,000 (95 % CI: 549,000-642,000) million in economic losses are attributable to total ambient PM 2.5 under the current emissions. We calculate that NH 3 emissions are associated with 11 % of the annual average PM 2.5 concentrations across South Asia. Changes in PM 2.5 concentrations follow a non-linear response to NH 3 emissions reductions, highlighting increased efficiency with 70 %-100 % reductions in NH 3 emissions reductions. We estimate that 247,000 (227,000-265,000) premature deaths and US$ 66,000 (61,000-71,000) million economic losses through this pathway can be attributed to NH 3 emissions. These findings confirm that in the current NH 3 -rich chemical environment of South Asia, the efficiency of PM 2.5 reduction is only moderately sensitive to the reduction in intensity of NH 3 emissions until emissions are cut very severely. Thus, SO 2 , NO x and NH 3 emissions controls need to be considered jointly for greater mitigation of ambient secondary PM 2.5 in South Asia., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: More than 80% of the Canadian population lives in urban settings. Urban areas usually bring exposure to poorer air quality, less access to green spaces, and higher building density. These environmental factors may endanger child development., Objective: To assess the relationship of urban environmental exposures during pregnancy with cognitive abilities, motor function, externalizing and internalizing symptoms in children., Method: We included 6,279 mother-child pairs from 3 Canadian population-based birth-cohorts (3D Cohort Study in Montreal, Quebec City, and Sherbrooke, AOF Study in Calgary, CHILD Study in Edmonton, Vancouver, Toronto, and Winnipeg). We estimated 7 environmental exposures of the built environment, surrounding greenness, and air pollution, around participant's home addresses during pregnancy. Validated neuropsychological tests were used to assess non-verbal and verbal abilities, gross and fine motor function, externalizing and internalizing symptoms at child's age 2 to 5 years. We assessed associations of each environmental exposure indicator with each of the 6 outcomes, using multivariate linear regression models. We conducted analyses separately by city of recruitment and combined estimates in meta-analyses., Results: Overall, urban environment during pregnancy was not associated with cognitive abilities (e.g., -0.81 non-verbal points 95 %CI [-2.10; 0.48] per 1 μg/m 3 increase in PM 2.5 ), motor function, or externalizing and internalizing symptoms. In individual cohorts, we found associations of some environmental exposures, in particular building density, fine particles, and nitrogen dioxide with non-verbal abilities, verbal abilities, and fine motor function, but overall confidence intervals in the meta-analyses included the null., Conclusion: We found no evidence of a relationship of prenatal built environment, surrounding greenness, and air pollution with cognitive abilities, motor functions or externalizing and internalizing symptoms in childhood. Urban environment has been shown to influence health across the lifecourse, however, specific exposures during pregnancy do not seem associated with poorer neurodevelopment in children of 2- to 5- year., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: Evidence is limited regarding the role of air pollution in acute lower respiratory infections among adults. We assessed the influence of long-term air pollution exposure on hospital admission for lower respiratory infections and whether there are vulnerable subgroups., Methods: We used a populational cohort in Catalonia, Spain, comprising 3,817,820 adults residing in Catalonia as of January 1, 2015. Air pollution exposure was assigned to individuaĺs residential address using locally-developed models. We characterized the concentration-response functions between long-term air pollution exposure and hospital admission for lower respiratory infections between 2015 and 2019. We assessed interaction between exposure and clinical and socio-economic factors on multiplicative and additive scales., Results: An interquartile range exposure increase was associated with an 8 % (95 % Confidence Interval: 5 %-11 %) for Nitrogen Dioxide, 10 % (95 % Confidence Interval: 8 %-13 %) for Particulate Matter with diameter equal to or smaller than 2.5 µm, 5 % (95 % Confidence Interval: 3 %-7%) for Particulate Matter with diameter equal to or smaller than 10 µm and 18 % (95 % Confidence Interval: 14 %-22%) for ozone (adjusted by Nitrogen Dioxide) increase in hospital admissions for respiratory infections. Concentration-response functions were non-linear, with steeper slopes at exposures below the median or at most extreme high values. Associations were consistently greater for individuals over 65 years or with hypertension diagnosis and males., Conclusions: Long-term exposure to air pollution was positively associated with hospital admission for lower respiratory infections. Individuals who were older than 65 years, hypertensive or male were most vulnerable., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Cathryn Tonne reports financial support was provided by Health Effects Institute. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2025 The Authors. Published by Elsevier Ltd.. All rights reserved.)

There is a body of evidence that ultrafine particles (UFP, those with diameters ≤ 100 nm) might have significant impacts on health. Accordingly, identifying sources of UFP is essential to develop abatement policies. This study focuses on urban Europe, and aims at identifying sources and quantifying their contributions to particle number size distribution (PNSD) using receptor modelling (Positive Matrix Factorization, PMF), and evaluating long-term trends of these source contributions using the non-parametric Theil-Sen's method. Datasets evaluated include 14 urban background (UB), 5 traffic (TR), 4 suburban background (SUB), and 1 regional background (RB) sites, covering 18 European and 1 USA cities, over the period, when available, from 2009 to 2019. Ten factors were identified (4 road traffic factors, photonucleation, urban background, domestic heating, 2 regional factors and long-distance transport), with road traffic being the primary contributor at all UB and TR sites (56-95 %), and photonucleation being also significant in many cities. The trends analyses showed a notable decrease in traffic-related UFP ambient concentrations, with statistically significant decreasing trends for the total traffic-related factors of -5.40 and -2.15 % yr -1 for the TR and UB sites, respectively. This abatement is most probably due to the implementation of European emissions standards, particularly after the introduction of diesel particle filters (DPFs) in 2011. However, DPFs do not retain nucleated particles generated during the dilution of diesel exhaust semi-volatile organic compounds (SVOCs). Trends in photonucleation were more diverse, influenced by a reduction in the condensation sink potential facilitating new particle formation (NPF) or by a decrease in the emissions of UFP precursors. The decrease of primary PM emissions and precursors of UFP also contributed to the reduction of urban and regional background sources., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Macro-scale distribution of air pollution concentrations is influenced by factors including geography, weather, industry, transport and regulation. Pollution sources are unevenly distributed, with some communities disproportionately impacted by higher emissions. This study separates the effects of deprivation from ethnicity as factors that influence proximity to pollution sources. We combine recent decadal census data (2021) on socioeconomic deprivation and detailed population ethnicity at fine scales (Lower Super Output layer Area, LSOA n = 1600 people) with a 1×1 km sector-resolved atmospheric emissions inventory for NO x and primary PM 2.5 in England. All 24 minoritised ethnic groups studied experienced higher average local NO x and PM 2.5 emissions than socio-economically matched populations in the majority 'White: English, Welsh, Scottish, Northern Irish or British' ethnic group. Chinese, Arab and Bangladeshi communities experienced the largest disparity in NO x , with weighted emissions 100%, 91%, 89% higher than white populations of matched deprivation status. Bangladeshi, Pakistani and Roma groups experienced on average 40%, 40%, 36% higher PM 2.5 emissions locally than matched white groups. For NO x the largest contributors leading to disparity, were road transport (48%), domestic combustion (23%) and industry (15%). For PM 2.5 the greatest contributors to disparity were domestic combustion (53%), road transport (19%), and industry (11%). Living near to road transport and in city centres are frequently cited as primary drivers of ethnicity and deprivation-based disparities, however the analysis identifies that industrial, domestic and off-road sources create issues of the same magnitude, and disparities remain in suburban settings, smaller towns and some rural areas., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Nathan Gray, Ally Lewis and Sarah Moller report financial support was provided by United Kingdom Department for Environment Food and Rural Affairs. Ally Lewis and Sarah Moller report a relationship with DEFRA Air Quality Expert Group that includes: consulting or advisory. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The rapid development of China's aviation industry has caused a rapid increase in airport PM 2.5 emissions. This study uses the Global Exposure Mortality Model (GEMM) to evaluate the monthly deaths caused by aircraft activities at 164 airports in China from 2015 to 2023, based on the PM 2.5 concentration of airport aircraft activities and the detection data of the China National Environmental Monitoring Center, including twenty age groups, six diseases, and gender. This paper presents three main conclusions. Firstly, aviation PM 2.5 emissions significantly impact mortality, with notable variations by year and season. The highest cumulative deaths are recorded in 2023, particularly in the third quarter, which peaked at 8,305 deaths. Despite the comparatively modest total of 11,604 deaths in 2022, a mere 0.2965 μg/m 3 increase in PM 2.5 concentration would precipitate an additional 39,138 deaths, representing a 1.05-fold rise from 2015. Secondly, the 80-84 age bracket exhibited the highest death proportion (16.51 %-18.73 %), while the 5-9 and 10-14 age groups had the lowest (0 %-0.13 %). Males aged 80-84 are the most affected demographic, with each 1 μg/m 3 increase in PM 2.5 leading to an additional 87 male deaths monthly in 2023, primarily from stroke and ischemic heart disease. In contrast, females only experienced 67 additional deaths per month from the same concentration increase. Lastly, airports in the economically vibrant Beijing-Shanghai-Guangzhou-Shenzhen region showed the highest mortality rates due to PM 2.5 emissions. Airports in eastern coastal areas are more severely impacted than those in central and western China, revealing a spatial clustering of high death tolls in developed regions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Poland is in the group of European countries with the most severe air quality and specific emission structure (over 80 % of PM2.5 emitted in residential combustion). In this work, we quantify the health impacts of PM2.5 concentrations in Poland using two chemical transport models (CTMs), WRF-Chem and EMEP4PL. The models were run for two years (2017 and 2018), which differed in meteorological conditions. The results show that the total number of premature deaths that could be avoided if the PM2.5 concentrations do not exceed the WHO recommended value of 5 μg m -3 exceeds 22,000 deaths for all model runs and meteorological years considered, with the lowest estimate at 22,447 (WRF-Chem model run for the year 2017; 95 % confidence intervals CI (95 % CI) 17121-25045) and the highest at 29,227 (95 % CI 22343 - 32572; EMEP4PL for the year 2018). These numbers are underestimated, as both CTMs underestimate the measured PM2.5 concentrations at site locations. The underestimation is the highest during the heating seasons and can be reduced if the emission of primary PM2.5 from residential combustion increases. The total number of estimated premature deaths is sensitive to chemical transport model selection and meteorological year. The selection of the meteorological year for the analysis may change the estimated number of premature deaths by 10 %. This change is significant compared to the estimated change in health impact due to the envisaged implementation of the Clean Air Program in Poland., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Studies revealed airports as a prominent source of ultrafine particles (UFP), which can disperse downwind to residential areas, raising health concerns. To expand our understanding of how air traffic-related emissions influence total particle number concentration (PNC) in the airport's surrounding areas, we conduct long-term assessment of airborne particulate exposure before and after relocation of air traffic from "Otto Lilienthal" Airport (TXL) to Berlin Brandenburg Airport "Willy Brandt" (BER) in Berlin, Germany. Here, we provide insights into the spatial-temporal variability of PNC measured in 16 schools recruited for Berlin-Brandenburg Air Study (BEAR). The results show that the average PNC in Berlin was 7900 ± 7000 cm -3 , consistent with other European cities. The highest median PNC was recorded in spring (6700 cm -3 ) and the lowest in winter (5100 cm -3 ). PNC showed a bi-modal increase during morning and evening hours at most measurement sites due to road-traffic emissions. A comparison between measurements at the schools and fixed monitoring sites revealed good agreement at distances up to 5 km. A noticeable decline in this agreement occurred as the distance between measurement sites increased. After TXL was closed, PNC in surrounding areas decreased by 30 %. The opposite trend was not seen after BER was re-opened after the COVID-lock-down, as the air traffic has not reached the full capacity yet. The analysis of particle number size distribution data showed that UFP number fraction exhibit seasonal variations, with higher values in spring and autumn. This can be explained by nucleation events, which notably affected PNC. The presented findings will play a pivotal role in forthcoming source attribution and epidemiological investigations, offering a holistic understanding of airports' impact on airborne pollutant levels and their health implications. The study calls for further investigations of air-traffic-related physical-chemical pollutant properties in areas found further away (> 10 km) from airports., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

The rapid expansion of the aviation sector raises concerns about air quality impacts within and around airports. Ultrafine particles (UFP, diameter < 100 nm) are of particular concern due to their potential adverse health effects. In this study, particle number concentrations (PNC), particle number size distribution (PNSD), and other ancillary pollutants such as particulate matter (PM), nitrogen oxides (NO X ), black carbon (BC), sulfur dioxide (SO 2 ), ozone (O 3 ), carbon monoxide (CO) and benzene, as well as organic markers and trace elements (in quasi-UFP) were measured at Barcelona-El Prat Airport (80 m and 250 m from the main taxiway and runway). Comparisons were made with an urban background (UB) location, and source apportionment of PNSD was performed using Positive Matrix Factorization (PMF). PNC inside the airport was nine-fold higher than the UB, and fifteen-fold higher when considering only nucleation mode particles (< 25 nm). Six sources contributing to PNC were identified inside the airport: Taxiing (48.7 %; mode diameter = 17 nm), Industrial/Shipping (7.4 %; mode diameter = 35 nm), Diesel (3.9 %; mode diameter = 64 nm), Regional recirculation (1.1 %; mode diameter = 100 nm), Photonucleation (16.6 %; mode diameter = 13 nm) and Takeoff (18.5 %; mode diameter = 23 nm). Due to the measurement location and prevailing wind patterns, no significant contributions from landings were detected. Chemical analysis of quasi-UFP collected on Electrical Low-Pressure Impactor (ELPI + ) filters (stages 2 to 6: 17-165 nm) revealed higher concentrations (> 2-fold) of Fe, Al, Cr, Cu, Mo, Mn, Pb, Ti, and Sb at the airport compared to the UB, with Al exhibiting the most pronounced disparity. Generally, PAH levels were low at both sites, although concentrations were higher at the airport relative to the UB. Overall, this study provides a comprehensive understanding of UFP within a major European airport, identifying the different sources contributing to PNC and PNSD., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Fulvio Amato reports financial support was provided by European Commission and Spanish Ministry of Science, Innovation and Universities.. Andres Alastuey reports financial support was provided by Spain Ministry of Science, Innovation and Universities. No If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Ambient air quality across the southeastern US has improved substantially in recent decades. However, emissions from prescribed burns remain high, which may pose a substantial health threat. We employed a multistage modeling framework to estimate year-round, long-term effects of prescribed burns on air quality and premature deaths. The framework integrates a chemical transport model with a data-fusion approach to estimate 24-h average PM 2.5 and maximum daily 8-h averaged O 3 (MDA8-O 3 ) concentrations attributable to prescribed burns for the period 2013-2020. The Global Exposure Mortality Model and a log-linear exposure-response function were used to estimate the premature deaths ascribed to long-term prescribed burn PM 2.5 and MDA8-O 3 exposure in ten southeastern states. Our results indicate that prescribed burns contributed on annual average 0.59 ± 0.20 µg/m 3 of PM 2.5 (∼10 % of ambient PM 2.5 ) over the ten southeastern states during the study period. On average around 15 % of the state-level ambient PM 2.5 concentrations were contributed by prescribed burns in Alabama (0.90 ± 0.15 µg/m 3 ), Florida (0.65 ± 0.19 µg/m 3 ), Georgia (0.91 ± 0.19 µg/m 3 ), Mississippi (0.65 ± 0.10 µg/m 3 ) and South Carolina (0.65 ± 0.09 µg/m 3 ). In the extensive burning season (January-April), daily average contributions to ambient PM 2.5 increased up to 22 % in those states. A large part of Alabama and Georgia experiences ≥3.5 µg/m 3 prescribed burn PM 2.5 over 30 days/year. Additionally, prescribed burns are responsible for an average increase of 0.32 ± 0.12 ppb of MDA8-O 3 (0.8 % of ambient MDA8-O 3 ) over the ten southeastern states. The combined effect of prescribed burn PM 2.5 exposure, population growth, and increase of baseline mortality over time resulted in a total of 20,416 (95 % confidence interval (CI): 16,562-24,174) excess non-accidental premature deaths in the ten southeastern states, with 25 % of these deaths in Georgia. Prescribed burn MDA8-O 3 was responsible for an additional 1,332 (95 % CI: 858-1,803) premature deaths in the ten southeastern states. These findings indicate significant impacts from prescribed burns, suggesting potential benefits of enhanced forest management strategies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Accurately estimating vehicle emissions is crucial for effective air quality management. As key data for emission inventory construction, emission factors (EFs) are influenced by vehicle usage characteristics and experience deterioration. Current deterioration models often employ single-factor approaches based on vehicle age or accumulated mileage, which fail to capture the effects of varying usage intensities within the same mileage or age intervals. This study addressed this limitation by developing a novel emission deterioration model that incorporates multi-dimensional usage characteristics and that utilizes a large-scale inspection and maintenance (I/M) dataset for light-duty gasoline vehicles (LDGVs). The modeling results reveal distinct deterioration patterns for different pollutants and highlight the synergistic effects of the usage duration and intensity: natural aging significantly impacts HC and NOx emissions, while CO emissions are more strongly affected by intensive use. Specifically, China V LDGVs that were driven 4 × 10 4  km/yr exhibited HC, CO, and NOx deterioration rates per mile that were approximately 4.1 % lower, 10.3 % higher, and 1.1 % higher, respectively, than those of vehicles driven 2 × 10 4  km/yr as the mileage increased from 5 × 10 4 km to 10 × 10 4 km. By leveraging timely emission data and explicitly accounting for usage intensity, this study corrected biases in local emission estimates by 5-85 % with respect to estimates from commonly used models. This framework enables the development of more effective control strategies and refinements to policy evaluations in megacities with I/M programs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: The UK is committed to achieve net zero greenhouse gas emissions by 2050. The suite of policies needed to reach net zero will lead to improvements in air quality and, consequently, could lessen air pollution inequalities. We assessed air pollution inequalities across different sociodemographic groups in England and Wales and explored how these might be differentially impacted by future air pollution projections in 2030 and 2040 under net zero policies., Methods: We employed a geodemographic classification approach to categorise neighbourhoods into five distinct clusters based on 2021 UK Census sociodemographic variables. We modelled fine particulate matter (PM 2.5 ) and nitrogen dioxide (NO 2 ) concentrations for the year 2019, and predicted concentrations in 2030 and 2040. We compared a business-as-usual (BAU) scenario and two policy pathways to achieve net zero currently considered by the UK government. We aggregated air pollution concentrations to the neighbourhood level and assessed differential neighbourhood-level concentrations across the geodemographic groups using descriptive statistics and box plots., Results: The Urban Central Professionals group experienced 14 µg/m 3 higher average NO 2 concentrations compared with the Rural Elderly group in 2019. Despite substantial improvements to air quality in 2030 and 2040 of up to 6.3 µg/m 3 for NO 2 based on BAU, and further reductions of up to 2.4 µg/m 3 NO 2 under net zero policies, the overall pattern of inequality persists, but is predicted to be less pronounced., Conclusions: Our findings demonstrate the effectiveness of targeted policies and innovations in reducing both air quality and greenhouse gas emissions and in bridging the environmental inequality gap. Our findings are essential to develop targeted communication campaigns to secure acceptance and willingness across the sociodemographic spectrum to support the significant behavioural changes needed to achieve net zero, by highlighting the wider co-benefits to the environment and health of such policies., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: [Co-authors Heather Walton and Mike Holland declare membership of the Committee on the Medical Effects of Air Pollutants reporting to the UK Department for Health and Social Care. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper]., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: The association between greenness exposure and semen quality and the underlying mechanism are unclear., Objectives: To assess the association between greenness exposure and semen quality and whether the association is mediated by air pollutant exposure., Methods: We collected data from 10,273 men in Zhejiang, China, whose wives received assisted reproductive technology from 2015 to 2021. The mean exposure concentrations of air pollutants and greenness indices (normalized difference vegetation index (NDVI) and the soil-adjusted vegetation index (SAVI)) in the 300 m, 400 m, 800 m, and 1000 m buffer zones were assessed from 0-90 days prior to semen testing on the basis of the patient's residential address. A multivariate linear mixed-effects model was used to evaluate the associations, and mediation analysis was used to investigate the influences of air pollutant exposure and body mass index (BMI) on the associations., Results: The average (standard deviation) age of the participants was 33.1 (5.2) years. After adjusting for confounders, progressive motility was positively associated with the NDVI 400m (β (95 % CI): 1.744 (0.834, 2.655)) and SAVI 400m (β (95 % CI): 1.484 (0.591, 2.377)). Furthermore, we found that NO 2 and CO exposure significantly mediated part of the association between greenness exposure and progressive motility. Similar results are observed in the sensitivity analysis., Conclusions: Our results suggest that greater greenness exposure is associated with higher semen quality and can be partially mediated by lower NO 2 and CO exposure levels., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The recognized importance of ambient fine particulate matter (PM 2.5 ), ozone (O 3 ), and nitrogen dioxide (NO 2 ) on human health has prompted the world to enact increasingly strict regulations on anthropogenic nitrogen oxides (NO x ) emissions. However, the health concerns from soil NO x , potentially driven by fertilizer input but conventionally categorized as natural sources, remain less studied. Here, we emphasize the underappreciated roles of soil NO x emissions on health burden attributable to short-term PM 2.5 , O 3 , and NO 2 exposure. Globally, we quantify acute health effects using machine-learning-based daily exposure estimates and identify influences of soil NO x emissions based on chemical transport model simulations. We find that 72.3% of the globe is affected by soil NO x emissions, whose contributions to short-term PM 2.5 , O 3 , and NO 2 pollution lead to 13.9 (95% Confidence Interval [CI]: 9.1-18.8), 26.0 (18.2-34.2), and 13.9 (10.3-17.5) thousand premature mortality, respectively, in 2019. With distinct variations in regions, seasons, and pollutants, soil NO x -originated air pollution poses a global health concern, particularly for developing regions and intensively agricultural areas. In response to the intensive fertilizer use, South Asia, Southern Sub-Saharan Africa, and Central Europe witness the largest soil NO x -related health burden of up to 1.6 (95% CI: 1.1-2.1) mortality per 100k population. The overall health risk peaks in May, with O 3 pollution typically dominating the soil NO x -attributable health burden during warm seasons and NO 2 or PM 2.5 during cold months. Our study highlights the necessity of dynamically adapted agricultural strategies for health-oriented multi-pollutant control, among which the improved use of synthetic fertilizers deserves priority under the ever-changing climate., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: Malignant brain tumours are rare, but are important to study because survival rates are low and few modifiable risk factors have been identified. Existing evidence suggests that outdoor ultrafine particles (UFPs; particulate matter < 100 nm; sometimes referred to as nanoparticles) can deposit in the brain and could encourage initiation and progression of cancerous tumours, but epidemiological data are limited., Methods: High-resolution estimates of outdoor UFP concentrations and size were linked to residential locations of approximately 1.5 million people in Montreal and Toronto, Canada from 2001 to 2015. Cox proportional hazards models were used to estimate associations between annual average outdoor UFPs and malignant brain tumour incidence while adjusting for potential confounding factors including other outdoor air pollutants., Findings: In total, 1365 incident brain tumour cases occurred during follow-up. Consistent positive associations were observed between long-term exposures to outdoor UFPs and brain tumour incidence with increased risk ranging from 10.5% (95% CI: -1.4, 24.0%) to 15.3% (95% CI: 0.4, 32.5%) per 10,000 particle/cm 3 increase. Long-term exposures to oxidant gases, black carbon, or fine particulate matter (PM 2.5 ) were not associated with increased brain tumour incidence., Interpretation: Our results suggest that long-term exposures to outdoor UFPs are associated with an increased risk of developing malignant brain tumours. On an absolute scale, the magnitude of this risk translates into approximately 24 additional cases per year per 10,000 particle/cm 3 increase in annual average outdoor UFPs in a hypothetical city of 3-million people., Funding: Canadian Institutes of Health Research (CIHR) Foundation Grant and The United States Health Effects Institute (HEI)., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: [Scott Weichenthal reports financial support was provided by Canadian Institutes of Health Research. Scott Weichenthal reports financial support was provided by United States Health Effects Institute. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.]., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Studies on air pollution and outcomes of in vitro fertilization (IVF) have focused on couples undergoing autologous IVF, in which it is challenging to disentangle maternal and paternal exposures during gametogenesis. We sought to evaluate the independent associations between air pollution exposure during oogenesis and spermatogenesis on fertilization and embryo quality in non-identified donor oocyte IVF cycles., Methods: Our study included 500 oocyte donors and 915 male recipient partners who contributed 1,095 oocyte thaw cycles (2008-2019). Daily ambient air pollutant exposure was estimated using spatio-temporal models based on residential address and averaged over folliculogenesis (i.e., three months prior to initiation of controlled ovarian stimulation), controlled ovarian stimulation, and spermatogenesis (i.e., 72 days prior to oocyte thaw). We used multivariable generalized estimating equations to estimate the adjusted odds ratios (aOR) and 95 % confidence intervals (CI) for an interquartile range increase in pollutant exposure in relation to the proportion of oocytes surviving thaw, oocytes fertilized, and usable embryos., Results: Oocyte donors with higher exposure to organic carbon (OC) (aOR = 0.86 95 %CI 0.79,0.94) and particulate matter < 10 µm (aOR = 0.69 95 %CI 0.54,0.90) during folliculogenesis had a lower proportion of oocytes surviving thaw. During ovarian stimulation, higher particulate matter < 2.5 µm (aOR = 0.78 95 %CI 0.66, 0.91), nitrate (aOR = 0.83 95 % CI 0.69,0.99), and OC (aOR = 0.86 95 % CI 0.80,0.93) exposure was associated with a lower proportion of surviving oocytes while nitrogen dioxide (aOR = 1.11 95 %CI 1.00,1.23) and ozone (aOR = 1.19 95 %CI 1.04,1.37) exposure was associated with a higher proportion of fertilized oocytes and usable embryos. Elemental carbon (aOR = 0.93 95 %CI 0.87,1.00) and OC (aOR = 0.95 95 %CI 0.90,1.00) exposure during spermatogenesis was associated with a slightly lower proportion of usable embryos. On the day of oocyte thaw, higher ambient OC at the IVF clinic was associated with lower oocyte survival and higher ozone was associated with lower fertilization., Conclusions: Both maternal and paternal air pollution exposures during gametogenesis have independent, largely detrimental, effects on early embryological outcomes., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Audrey J. Gaskins reports financial support was provided by National Institute of Environmental Health Sciences. Zsolt P. Nagy reports a relationship with CooperSurgical Inc that includes: board membership. Zsolt P. Nagy reports a relationship with Prelude Fertility Inc that includes: equity or stocks. Daniel B. Shapiro reports a relationship with Prelude Fertility Inc that includes: equity or stocks. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

California's diverse geography and meteorological conditions necessitate models capturing fine-grained patterns of air pollution distribution. This study presents the development of high-resolution (100 m) daily land use regression (LUR) models spanning 1989-2021 for nitrogen dioxide (NO 2 ), fine particulate matter (PM 2.5 ), and ozone (O 3 ) across California. These machine learning LUR algorithms integrated comprehensive data sources, including traffic, land use, land cover, meteorological conditions, vegetation dynamics, and satellite data. The modeling process incorporated historical air quality observations utilizing continuous regulatory, fixed site saturation, and Google Streetcar mobile monitoring data. The model performance (adjusted R 2 ) for NO 2 , PM 2.5 , and O 3 was 84 %, 65 %, and 92 %, respectively. Over the years, NO 2 concentrations showed a consistent decline, attributed to regulatory efforts and reduced human activities on weekends. Traffic density and weather conditions significantly influenced NO 2 levels. PM 2.5 concentrations also decreased over time, influenced by aerosol optical depth (AOD), traffic density, weather, and land use patterns, such as developed open spaces and vegetation. Industrial activities and residential areas contributed to higher PM 2.5 concentrations. O 3 concentrations exhibited no significant annual trend, with higher levels observed on weekends and lower levels associated with traffic density due to the scavenger effect. Weather conditions and land use, such as commercial areas and water bodies, influenced O 3 concentrations. To extend the prediction of daily NO 2 , PM 2.5 , and O 3 to 1989, models were developed for predictors such as daily road traffic, normalized difference vegetation index (NDVI), Ozone Monitoring Instrument (OMI)-NO2, monthly AOD, and OMI-O3. These models enabled effective estimation for any period with known daily weather conditions. Longitudinal analysis revealed a consistent NO 2 decline, regulatory-driven PM 2.5 decreases countered by wildfire impacts, and spatially variable O 3 concentrations with no long-term trend. This study enhances understanding of air pollution trends, aiding in identifying lifetime exposure for statewide populations and supporting informed policy decisions and environmental justice advocacy., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: The current limit on NO 2 concentrations of 40 μg/m 3 , set by the European Union, has been regularly exceeded in Munich, Germany. This limit will likely be reduced towards the WHO recommended target of 10 μg/m3. Against this backdrop, the city implemented a selective diesel vehicle ban within the existing low-emission zone in February 2023, targeting Euro 4 and older diesel vehicles. Our study investigated the effect of Munich's selective diesel vehicle ban on NO 2 concentrations, focusing on the half-year period following its implementation., Methods: Our study utilized a synthetic control approach (primary analysis) and a controlled interrupted time series approach (secondary analysis). These quasi-experimental methodologies create a 'counterfactual' no-intervention scenario, enabling comparison between observed and counterfactual scenarios to estimate an intervention effect. We employed historical controls, using routine data from multiple monitoring stations located within and outside the low-emission zone for 2014 to 2022, and considered possible confounders., Results: NO 2 concentrations within Munich's low-emission zone showed overall declining trends from August 2014 to July 2023. Effects of the selective diesel vehicle ban were small and wide confidence intervals indicate large uncertainty in the magnitude and direction of the effect. At Landshuter Allee, the average intervention effect was -2.67 μg/m 3 (95 %-CI = [-12.72; 7.38]), at Stachus it was -2.74 μg/m 3 (95 %-CI = [-9.91; 4.42]), and at Lothstrasse it was -1.03 μg/m 3 (95 %-CI = [-7.75; 5.69]). The secondary analysis confirmed these findings, reinforcing uncertainty about the effect of the intervention., Conclusion: Our study suggests that Munich's selective diesel vehicle ban had a limited effect on lowering NO 2 concentrations. Possible explanations include the ban's focus on Euro 4 and older diesel vehicles, many exemptions to the selective ban, and unclear enforcement. This highlights that comprehensive approaches and ongoing, well-designed monitoring and evaluation are crucial for addressing urban air pollution and protecting public health., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: ER declares owning a Diesel Euro 4 vehicle. The other authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Introduction: Prenatal and early-life exposure to air pollution and extreme temperatures are associated with childhood asthma and wheeze. However, potential windows of susceptibility and their sex-specific and interactive effects have not been fully elucidated. We aimed to identify critical windows of susceptibility and evaluate sex-specific effects in these associations, and evaluate exposure interactions., Methods: We analyzed data from 468 mother-child pairs enrolled in the PROGRESS birth cohort in Mexico City. Daily residential levels of PM 2.5 , NO 2 , and temperature were generated from our validated spatiotemporally resolved models from conception to age 4 years. Childhood asthma and wheeze outcomes were collected at 4-6 and 7-8 years. Distributed lag nonlinear models (DLNMs) were used to identify susceptible windows for prenatal weekly-specific and postnatal monthly-specific associations of air pollution and temperature with respiratory outcomes adjusting for covariates. To evaluate sex-specific effects, DLNMs were stratified. Joint effects were assessed using relative excess risk due to interaction and attributable proportion., Results: Mid-gestation was a critical window for both PM 2.5 (weeks 20-28, cumulative OR: 1.18 [95% CI: 1.01, 1.37]; weeks 19-26, cumulative OR: 1.18 [95% CI: 1.02, 1.36]) and NO 2 (weeks 18-25, cumulative OR: 1.16 [95% CI: 1.02, 1.31]) exposure, associated with higher odds of wheeze. Postnatal exposure to PM 2.5 and NO 2 during the first year of life was also linked to higher odds of wheeze. The warmer and colder temperatures showed mixed effects on respiratory outcomes. We observed a synergistic interaction between high PM 2.5 and high temperature exposure during the first year of life, associated with higher odds of current wheeze. The associations of prenatal air pollution and temperature exposure with respiratory outcomes were more pronounced in males., Conclusions: Early-life air pollution exposure contributes to the development of childhood asthma and wheeze, while exposure to temperature showed mixed associations with respiratory outcomes., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Accurate air quality forecasting is crucial for public health, environmental monitoring and protection, and urban planning. However, existing methods fail to effectively utilize multi-scale information, both spatially and temporally. There is a lack of integration between individual monitoring stations and city-wide scales. Temporally, the periodic nature of air quality variations is often overlooked or inadequately considered. To overcome these limitations, we conduct a thorough analysis of the data and tasks, integrating spatio-temporal multi-scale domain knowledge. We present a novel Multi-spatial Multi-temporal air quality forecasting method based on Graph Convolutional Networks and Gated Recurrent Units (M2G2), bridging the gap in air quality forecasting across spatial and temporal scales. The proposed framework consists of two modules: Multi-scale Spatial GCN (MS-GCN) for spatial information fusion and Multi-scale Temporal GRU (MT-GRU) for temporal information integration. In the spatial dimension, the MS-GCN module employs a bidirectional learnable structure and a residual structure, enabling comprehensive information exchange between individual monitoring stations and the city-scale graph. Regarding the temporal dimension, the MT-GRU module adaptively combines information from different temporal scales through parallel hidden states. Leveraging meteorological indicators and four air quality indicators, we present comprehensive comparative analyses and ablation experiments, showcasing the higher accuracy of M2G2 in comparison to nine currently available advanced approaches across all aspects. The improvements of M2G2 over the second-best method on RMSE of 72-h future predictions are as follows: PM 2.5 : 6%∼10%; PM 10 : 5%∼7%; NO 2 : 5%∼16%; O 3 : 6%∼9%. Furthermore, we demonstrate the effectiveness of each module of M2G2 by ablation study. We conduct a sensitivity analysis of air quality and meteorological data, finding that the introduction of O 3 adversely impacts the prediction accuracy of PM 2.5 ., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Introduction: A causal link between air pollution exposure and cardiovascular events has been suggested. However fewer studies have investigated the shape of the associations at low levels of air pollution and identified the most important temporal window of exposure. Here we assessed long-term associations between particulate matter < 2.5 µm (PM 2.5 ) at low concentrations and multiple cardiovascular endpoints using the UK Biobank cohort., Methods: Using data on adults (aged > 40) from the UK Biobank cohort, we investigated the associations between 1-year, 3-year and 5-year time-varying averages of PM 2.5 and incidence of major adverse cardiovascular events (MACE), myocardial infarction (MI), heart failure, atrial fibrillation and flutter and cardiac arrest. We also investigated outcome subtypes for MI and stroke. Events were defined as hospital inpatient admissions. We fitted Cox proportional hazard regression models applying extensive control for confounding at both individual and area level. Finally, we assessed the shape of the exposure-response functions to assess effects at low levels of exposure., Results: We analysed data from 377,736 study participants after exclusion of prevalent subjects. The average follow-up (2006-2021) was 12.9 years. We detected 19,353 cases of MACE, 6,562 of acute MI, 6,278 of heart failure, 1,258 for atrial fibrillation and flutter, and 16,327 for cardiac arrest. Using a 5-year exposure window, we detected positive associations (for 5 μg/m 3 increase in PM 2.5 ) for 5-point MACE of [1.12 (95 %CI: 1.00-1.26)], heart failure [1.22 (1.00-1.50)] and cardiac arrest [1.16 (1.03-1.31)]. We did not find any association with acute MI, while non-ST-elevation MI was associated with the 1-year exposure window [1.52 (1.12-2.07)]. The assessment of the shape of the exposure-response relationships suggested that risk is approximately linear for most of the outcomes., Conclusions: We found positive associations between long-term exposure to PM 2.5 and multiple cardiovascular outcomes for different exposure windows. The cardiovascular risk tends to rise even at exposure concentrations below 12-15 μg/m 3 , indicating high risk below UK national and international thresholds., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Both ambient fine particulate matter (PM 2.5 ) and aging are important urban concerns. However, the associations between PM 2.5 constituents and the acceleration of aging (AA) remain unclear. We included 16,051 adults (aged 25-80 years) with 19,252 medical observations in Taiwan during 2008-2017. 2-year average PM 2.5 and its five major constituents were assessed using a two-stage machine learning model at a resolution of 1 km 2 . AA was determined by the difference between the Klemera-Doubal biological age and chronological age. A linear mixed model (LMM) with inverse probability weights was used to examine the associations between AA and air pollution. In a semi-randomized study design, we applied a post-matching LMM to assess the impacts of changes in air pollution exposure on AA. Each interquartile range increase in ambient PM 2.5 , SO 4 -2 , NO 3 - , NH 4 + , organic matters (OM), and black carbon (BC) was associated with a 0.20 (95 %confidence interval [CI]: 0.17-0.24), 0.19 (0.15-0.23), 0.14 (0.11-0.18), 0.21 (0.17-0.24), 0.22 (0.19-0.26) and 0.25 (0.21-0.28) year increase in AA, respectively. BC was generally associated with the greatest increase in AA as compared to other constituents. We did not find evident thresholds in their concentration-response associations. Participants exposed to increased levels of PM 2.5 , SO 4 -2 , NO 3 - , NH 4 + , OM, and BC experienced an increase in AA of 0.11 (-0.07-0.29), 0.20 (0.02-0.39), 0.15 (-0.02-0.33), 0.12 (-0.07-0.31), 0.24 (0.07-0.41), and 0.30 (0.07-0.52) years, respectively, compared to those exposed to decreased/unchanged levels. Long-term exposure to ambient PM 2.5 and its constituents may accelerate biological aging among Chinese adults. Exposed to increased levels may further aggregate the aging process. This study suggests that reducing exposure to air pollution is beneficial, even for residents within moderately-to-highly polluted regions, such as Taiwan. Rigorous regulation of PM 2.5 and its constituents may prevent the acceleration of biological age., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: Climate change is expected to elevate exposure to several environmental health risk factors, including extreme environmental temperatures, air pollution and airborne allergenic pollen. Given their interconnected effects on respiratory and cardiovascular diseases, it is crucial to evaluate these exposures simultaneously. Yet, comprehensive efforts to do so remain limited. This research aims to develop an approach using modelled data, in conjunction with health-based threshold values, to assess whether, where and when there is simultaneous threshold exceedance of heat, air pollution and airborne allergenic pollen in Europe., Methods: Hourly exposure data for the three stressors were sourced from three models (air pollution: LOTOS-EUROS, pollen: Copernicus Atmosphere Monitoring Service, meteorological conditions: ECMWF) for 2021 and 2022. Thresholds for each stressor that indicate the boundary of acceptable limits were based on officially established tresholds or literature recommendations. The result is a 0.1°x0.1° resolution grid (approximately 10 km x 10 km) for each stressor, with each cell representing whether exposure met or exceeded the threshold., Findings: Simultaneous threshold exceedance of air pollution and heat is occurring in various degrees throughout Europe. In the summer of 2022, the exceedances ranged from below 1% in large parts of Northern Europe to as much as 25% of the time in the Mediterranean area. An assessment of monthly threshold exceedance patterns shows a dynamic and changing co-exposure pattern across the year, which differs per region., Interpretation: This work lays out a robust approach to assess simultaneous threshold exceedances of multiple environmental health risk stressors. This approach can guide policy makers in pinpointing high-risk areas particularly vulnerable to simultaneous threshold exceedances, and develop mitigation strategies for those areas., Funding: Internal funding from TNO., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

The transport of atmospheric pollutants plays a pivotal role in regional air pollution, highlighting critical concerns over the unequal health outcomes that arise from such transport. While previous researches predominantly focused on key areas in the battle against air pollution, the intensification of control measures necessitates a national perspective to comprehend the health impacts due to pollution transport. Our study establishes an integrated assessment framework that combine an emission-concentration response surface model with a health impact evaluation model to analyse the nationwide health impacts of PM 2.5 and O 3 pollution transport across China's 31 provinces. We found that, interprovincial transport of PM 2.5 and O 3 contributed to 747,000 and 110,000 deaths respectively in 2017, which amounts to 38% and 48% of deaths caused by total anthropogenic emissions. North, East, and Central China together contribute 82% and 69% to the health impacts caused by regional PM 2.5 and O 3 transport respectively, and the transport among these three regions is also significant. The analysis of interprovincial health impact transport shows that, for PM 2.5 , the top contributors are Hebei, Shandong, Henan, Anhui, and Jiangsu, with the most affected being Henan, Shandong, Jiangsu, Hebei, and Guangdong. Regarding O 3 , Shandong, Hebei, Henan, Jiangsu, and Anhui contribute the most, while Henan, Shandong, Hebei, Jiangsu, and Anhui are the most affected. This study can shed lights on regional control strategies by prioritizing control areas based on the health impact of air pollution transport in China., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Changes in energy and environmental policies along with changes in the energy markets of New York State over the past two decades, have spurred interest in evaluating their impacts on emissions from various energy generation sectors. This study focused on quantifying these effects on VOC (volatile organic compounds) emissions and their subsequent impacts on air quality within the New York City (NYC) metropolitan area. NYC is an EPA nonattainment region for ozone (O 3 ) and likely is a VOC limited region. NYC has a complex coastal topography and meteorology with low-level jets and sea/bay/land breeze circulation associated with heat waves, leading to summertime O 3 exceedances and formation of secondary organic aerosol (SOA). To date, no comprehensive source apportionment studies have been done to understand the contributions of local and long-range sources of VOCs in this area. This study applied an improved Positive Matrix Factorization (PMF) methodology designed to incorporate atmospheric dispersion and photochemical reaction losses of VOCs to provide improved apportionment results. Hourly measurements of VOCs were obtained from a Photochemical Assessment Monitoring Station located at an urban site in the Bronx from 2000 to 2021. The study further explores the role of VOC sources in O 3 and SOA formation and leverages advanced machine learning tools, XGBoost and SHAP algorithms, to identify synergistic interactions between sources and provided VOC source impacts on ambient O 3 concentrations. Isoprene demonstrated a substantial influence in the source contribution of the biogenic factor, emphasizing its role in O 3 formation. Notable contributions from anthropogenic emissions, such as fuel evaporation and various industrial processes, along with significant traffic-related sources that likely contribute to SOA formation, underscore the combined impact of natural and human-made sources on O 3 pollution. Findings of this study can assist regulatory agencies in developing appropriate policy and management initiatives to control O 3 pollution in NYC., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Over a span of 34 years (1987-2019), an in-depth analysis of PM 10 , SO 2 , and NO 2 trends across India was conducted using data from the National Ambient Air Quality Monitoring Programme's manual monitoring stations in 336 cities. The study encompassed six geographical regions over three time blocks, revealing a correlation between the expansion of monitoring networks and the nation's economic growth. Regions like the densely populated Indo-Gangetic Plains (IGP) and Central India consistently hosted more monitoring stations, while the Himalayan and Northeast regions saw substantial increases from initial scarcity. SO 2 concentrations showed a declining trend, while NO 2 levels remained relatively stable with intermittent fluctuations. Conversely, national average PM 10 concentrations exhibited an upward trajectory, notably spiking by 128 % between 2006 and 2009 due to economic activities, construction, network expansion, the 2009 drought, and heightened coal consumption. Spatially, pollutant concentrations across three blocks demonstrated improved SO 2 levels, several cities exceeding NO 2 standards, and persistently high PM 10 levels in the IGP. PM 10 levels in block 3 were lower than in block 2, reflecting effective policy interventions. State rankings, however, did not consistently reflect pollutant trends across blocks. Regionally, the IGP consistently had the highest PM 10 concentrations, while the Northeast recorded the lowest. Population-weighted exposure levels indicated an overall increase in public exposure to PM 10 . Analysis of major city per region aligned with national trends, as evidenced by Delhi (IGP), Guwahati (Northeast), Vadodara (Northwest), and Bhopal (Central) showing increased PM 10 concentrations since 2006, followed by intermittent declines. In contrast, Shimla (Himalayan) and Chennai (Southern) exhibited distinct patterns. Major industrial cities such as Parwanoo, Bongaigaon, Angul and Talcher, and Visakhapatnam mirrored national trends, with PM 10 levels rising since 2009, highlighting the significant impact of industrial activities on air quality. This research underscores the need for targeted, effective mitigation strategies based on spatial and temporal pollutant trends., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Beijing, with the highest number of motor vehicles in China, significantly contributes to O 3 pollution through substantial NO x and VOC emissions in the on-road transportation sector. Understanding the unique impact of emissions from different vehicle types on O 3 levels is crucial for developing targeted strategies for O 3 pollution. This study applied the Community Multiscale Air Quality Modeling System (CMAQ) to comprehensively investigate the impacts of emissions from different vehicle types on O 3 levels in various regions of Beijing and to provide valuable insights into source contributions and formation processes. The results revealed that various vehicle types exhibited different spatial-temporal emission patterns, with medium-heavy duty trucks (HDT) and mini-light passenger vehicles (LDPV) identified as the primary contributors to NO x (36.1 %) and VOC (57.6 %) emissions. Using the Integrated Source Apportionment Method (ISAM) coupled in CMAQ, we found the total vehicle emissions contributed to over 20 % of daily maximum 8-h average O 3 (MDA8 O 3 ) concentration, ranked as the second largest contributor after regional transport. Contributions to O 3 formation from LDPV and medium-large passenger vehicles (MDPV) were 2.6-4.0 and 4.2-6.8 ppb and mainly concentrated in urban areas, while the contributions from mini-light duty trucks (LDT) and HDT were 3.5-4.8 and 3.7-6.2 ppb and mainly concentrated in suburban areas. Through scenario analysis that removed emissions from specific types of vehicles, we found removing LDPV emissions led to decreases in daytime O 3 concentration by 0.3-3.8 ppb. In contrast, removing MDPV emissions led to notable O 3 increases by 4.0-11.8 ppb at rush hours. Removing LDT and HDT emissions resulted in 0.6-8.0 ppb increases in nocturnal O 3 concentrations while 0.8-2.0 ppb decreases during the afternoon. This research highlights the necessity of tailoring control strategies for different vehicle types to effectively reduce O 3 levels in Beijing and provides useful information for decision-makers to formulate effective measures of vehicle management in the future., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Chemicals emitted from industrial facilities include known or suspected mammary carcinogens and endocrine disruptors, but epidemiologic studies are limited. We evaluated associations between air emissions of multiple carcinogenic chemicals and postmenopausal breast cancer risk in a large prospective U.S., Methods: We used the U.S. Environmental Protection Agency's Toxics Release Inventory to estimate historical airborne emissions (1987-1995) of 19 known and probable carcinogens for participants enrolled (1995-1996) in the NIH-AARP Diet and Health Study. Among 170,402 women, 15,124 breast cancers were diagnosed through 2018. We constructed inverse distance- and wind-weighted average emissions metrics within 1, 2, 5, and 10 km of the enrollment address for each chemical. We estimated multivariable adjusted HRs and 95 % CIs for categories (quartiles, tertiles, medians) of each chemical in association with breast cancer overall and separately by type (invasive, ductal carcinoma in situ) and estrogen receptor (ER) status., Results: We observed an association between benzene emissions and breast cancer risk that was strongest at 1 km (HR Q4 vs. non-exposed = 2.06, 95 %CI: 1.34-3.17; p-trend = 0.001). The magnitude of the association weakened with increasing distance (2 km HR Q4 vs. non-exposed = 1.17, 95 %CI=0.92-1.49; p-trend = 0.19; 5 km HR Q4 vs. non-exposed = 1.05, 95 %CI=0.94-1.16; p-trend = 0.37; 10 km HR Q4 vs. non-exposed = 0.95, 95 %CI=0.89-1.02; p-trend = 0.19) and appeared to be most relevant for invasive rather than intraductal disease. Overall risk was also elevated for vinyl chloride at 5 km (HR ≥median vs. non-exposed = 1.20, 95 %CI=1.01-1.43; p-trend = 0.04), but not 2 km or 10 km. We observed suggestive associations for asbestos, trichloroethylene, and styrene in different subgroup analyses, but risk patterns were not clear across distances. Associations with other chemicals were generally null, with limited evidence of heterogeneity by disease type or ER status., Conclusions: An increased risk of breast cancer associated with relatively high levels of industrial benzene emissions warrants additional study, particularly among participants with diverse sociodemographic characteristics that live in areas with higher density of industrial facilities., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Published by Elsevier Ltd.)

Background: There is increasing evidence that air pollution and noise may have detrimental psychological impacts, but there are few studies evaluating adolescents, ground-level ozone exposure, multi-exposure models, or metrics beyond outdoor residential exposure. This study aimed to address these gaps., Methods: Annual air pollution and traffic noise exposure at home and school were modelled for adolescents in the Greater London SCAMP cohort (N=7555). Indoor, outdoor and hybrid environments were modelled for air pollution. Cognitive and mental health measures were self-completed at two timepoints (baseline aged 11-12 and follow-up aged 13-15). Associations were modelled using multi-level multivariate linear or ordinal logistic regression., Results: This is the first study to investigate ground-level ozone exposure in relation to adolescent executive functioning, finding that a 1 interquartile range increase in outdoor ozone corresponded to -0.06 (p < 0.001) z-score between baseline and follow-up, 38 % less improvement than average (median development + 0.16). Exposure to nitrogen dioxide (NO 2 ), 24-hour traffic noise, and particulate matter < 10 µg/m 3 (PM 10 ) were also significantly associated with slower executive functioning development when adjusting for ozone. In two-pollutant models, particulate matter and ozone were associated with increased externalising problems. Daytime and evening noise were associated with higher anxiety symptoms, and 24-hour noise with worse speech-in-noise perception (auditory processing). Adjusting for air pollutants, 24-hour noise was also associated with higher anxiety symptoms and slower fluid intelligence development., Conclusions: Ozone's potentially detrimental effects on adolescent cognition have been overlooked in the literature. Our findings also suggest harmful impacts of other air pollutants and noise on mental health. Further research should attempt to replicate these findings and use mechanistic enquiry to enhance causal inference. Policy makers should carefully consider how to manage the public health impacts of ozone, as efforts to reduce other air pollutants such as NO 2 can increase ozone levels, as will the progression of climate change., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Declining total fertility rates have been observed in low- and middle-income countries (LMICs). However, it remains unclear if this trend is related to a reduction in fecundity of general population. Research evidence on contributing factors to fecundity reduction is also limited. We aimed to first estimate couple fecundity in LMICs and then investigate its association with ambient particulate matter (PM) exposure., Methods: Using the information from Demographic and Health Surveys between 2003 and 2019, we estimated median time to pregnancy (TTP) and infertility prevalence across 30 LMICs, by employing a current duration approach. Individual PM (PM 1 , PM 2.5 , and PM 10 ) exposure during the period of 'at risk' of pregnancy was assessed by months. An accelerated failure model was used to elucidate the association between monthly time-varying PM exposure and TTP. Subsequently, we estimated the prolonged TTP attributable to PM exposures above the World Health Organization (WHO)'s recommended air quality level in 2021., Results: Within the study regions, median TTP ranged from 6.90 (95 % CI 6.02-7.87) months in Latin America & Caribbean to 10.29 (95 % CI 9.28-11.36) months in East Asia & Pacific, with corresponding infertility prevalence varying from 33 % (95 % CI 29 %-36 %) to 44 % (95 % CI 41 %-48 %). Our estimations indicated that TTP was 1.08 (95 % CI: 0.99-1.18), 1.12 (95 % CI 1.06-1.19), and 1.05 (95 % CI 1.03-1.07) times longer for every 10 μg/m 3 increment in PM 1 , PM 2.5 , and PM 10 , respectively. The prolonged TTP attributable to PM exposures surpassing the WHO guideline ranged from 0.11 to 2.81 months across the studied regions., Discussion: Ambient particulate matter is identified as a potential contributing factor to impaired fecundity in general population of LMICs. The findings underscore the importance of coordinated efforts to control ambient air pollution to mitigate the risk of fecundity reduction among the general population., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Traffic-related air pollution (TRAP) is a major contributor to urban pollution and varies sharply at the street level, posing a challenge for air quality modeling. Traditional land use regression models combined with data from fixed monitoring stations may be unable to predict and characterize fine-scale TRAP, especially in complex urban environments influenced by various features. This study aims to estimate fine-scale (50 m) concentrations of nitrogen oxides (NO and NO₂) in Hong Kong using a deep learning (DL) structured model., Methods: We collected data from mobile air quality sensors on buses and crowd-sourced Google real-time traffic status as a proxy for real-time traffic emissions. Our DL model was compared with existing machine learning models to assess performance improvements. Using an interpretable machine learning method, we hierarchically evaluated the global, local, and interaction effects for different features., Results: Our DL model outperformed existing machine learning models, achieving R 2 values of 0.72 for NO and 0.69 for NO₂. The incorporation of traffic status as a key predictor improved model performance by 9% to 17%. The interpretable machine learning method revealed the importance of traffic-related features and their pairwise interactions., Conclusion: The results indicate that traffic-related features significantly contribute to TRAP and provide insights and guidance for urban planning. By incorporating crowd-sourced Google traffic information, we assessed traffic abatement scenarios that could inform targeted strategies for improving urban air quality., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

South Korea and China have implemented increasingly stringent mitigation measures to reduce the health risks from PM 2.5 exposure, jointly conducting a ground-based air quality observation study in Northeast Asia. Dispersion normalized positive matrix factorization (DN-PMF) was used to identify PM 2.5 sources in Seoul and Beijing and assess the effectiveness of the seasonal management programs (SMPs) through a comparative study. Samples were collected during three periods: January-December 2019, September 2020-May 2021, and July 2021-March 2022. In Seoul, ten sources were resolved (Secondary nitrate: 8.67 μg/m 3 , 34 %, Secondary sulfate: 5.67 μg/m 3 , 22 %, Motor vehicle: 1.83 μg/m 3 , 7.2 %, Biomass burning: 2.30 μg/m 3 , 9.1 %, Residual oil combustion: 1.66 μg/m 3 , 6.5 %, Industry: 2.15 μg/m 3 , 8.5 %, Incinerator: 1.39 μg/m 3 , 5.5 %, Coal combustion: 0.363 μg/m 3 , 1.4 %, Road dust/soil: 0.941 μg/m 3 , 3.7 %, Aged sea salt: 0.356 μg/m 3 , 1.4 %). The SMP significantly decreased PM 2.5 mass concentrations and source contributions of motor vehicle, residual oil combustion, industry, coal combustion, and biomass burning sources (p-value < 0.05). For Seoul, the reduction effects of the SMPs were evident even considering the influence of the natural meteorological variations and the responses to COVID-19. In Beijing, nine sources were resolved (Secondary nitrate: 12.6 μg/m 3 , 28 %, Sulfate: 8.27 μg/m 3 , 18 %, Motor vehicle: 3.77 μg/m 3 , 8.4 %, Biomass burning: 2.70 μg/m 3 , 6.0 %, Incinerator: 4.50 μg/m 3 , 10 %, Coal combustion: 3.52 μg/m 3 , 7.8 %, Industry: 5.01 μg/m 3 , 11 %, Road dust/soil: 2.92 μg/m 3 , 6.5 %, Aged sea salt: 1.63 μg/m 3 , 3.6 %). Significant reductions in PM 2.5 mass concentrations and source contributions of industry, coal combustion, and incinerator (p-value < 0.05) were observed, attributed to the SMP and additional measures enforced before the 2022 Beijing Winter Olympics. Unlike comparing PM 2.5 mass concentration variations using conventional methods, investigation of the source contribution variations of PM 2.5 by using DN-PMF can provide a deeper understanding of the effectiveness of the air quality management policies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Background: Urban neighbourhood environments may impact older adults' cognitive health. However, longitudinal studies examining key environmental correlates of cognitive health are lacking. We estimated cross-sectional and longitudinal associations of neighbourhood built and natural environments and ambient air pollution with multiple cognitive health outcomes in Australian urban dwellers aged 60+ years., Methods: The study included 1160 participants of the PATH Through Life study (60+ cohort) who were followed up for 12 years (four assessments; 2001/02 to 2013/15) and with data on socio-demographics, health, cognitive functions and diagnoses, and full residential address. Neighbourhood environmental features encompassed population and street-intersection densities, non-commercial land use mix, transit points, presence of blue space, percentages of commercial land, parkland and tree cover, and annual average PM 2.5 and NO 2 concentrations. All exposures except for tree cover were assessed at two time points. Generalised additive mixed models estimated associations of person-level average, and within-person changes in, exposures with cognitive functions. Multi-state hidden Markov models estimated the associations of neighbourhood attributes with transitions to/from mild cognitive impairment (MCI)., Results: Dense, destination-rich neighbourhoods were associated with a lower likelihood of transition to MCI and reversal to no MCI. Positive cross-sectional and longitudinal associations of non-commercial land use mix, street intersection density and percentage of commercial land were observed especially with global cognition and processing speed. While access to parkland and blue spaces were associated with a lower risk of transition to MCI, the findings related to cognitive functions were mixed and supportive of an effect of parkland on verbal memory only. Higher levels of PM 2.5 and NO 2 were consistently associated with steeper declines and/or decreases in cognitive functions and worse cognitive states across time., Conclusion: To support cognitive health in ageing populations, neighbourhoods need to provide an optimal mix of environmental complexity, destinations and access to the natural environment and, at the same time, minimise ambient air pollution., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Epidemiological evidence on the association between wildfire-specific fine particulate matter (PM 2.5 ) and its carbonaceous components with perinatal outcomes is limited. We aimed to examine the short-term effects of wildfire-specific PM 2.5 and its carbonaceous components on perinatal outcomes., Methods: A multicentre cohort of 9743 singleton births during the wildfire seasons from 1 September 2009 to 31 December 2015 across six cities in New South Wales, Australia were linked with daily wildfire-specific PM 2.5 and carbonaceous components (organic carbon and black carbon). Adjusted distributed lag Cox regression models with spatial clustering were performed to estimate daily and cumulative adjusted hazard ratios (aHRs) during the last four gestational weeks for preterm birth, stillbirth, nonvertex presentation, low 5-min Apgar score, special care nursery/neonatal intensive care unit (SCN/NICU) admission, and caesarean section., Results: Daily aHRs per 10 µg/m 3 PM 2.5 showed nearly inverted 'U'-shaped positive associations and daily cumulative aHRs that increased with increasing duration of the exposures. The aHRs for lag 0-6 days were 1.17 (95 % CI: 1.04, 1.32) for preterm birth, 1.40 (95 % CI: 1.11, 1.78) for stillbirth, 1.20 (95 % CI: 1.08, 1.33) for nonvertex presentation, 1.12 (95 % CI: 0.93, 1.35) for low 5-min Apgar score, 0.99 (95 % CI: 0.83, 1.19) for SNC/NICU admission, and 1.01 (95 % CI: 0.94, 1.08) for caesarean section. Organic carbon and black carbon components for lag 0-6 days showed positive associations. The highest component-specific aHRs were 1.09 (95 % CI: 1.03, 1.15) and 4.57 (95 % CI: 1.96, 10.68) for stillbirth per 1 µg/m 3 organic carbon and black carbon, respectively. The subgroups identified as most vulnerable were female births, births to mothers with low socioeconomic status, and births to mothers with high biothermal exposure., Conclusions: Positive associations of short-term wildfire-specific PM 2.5 exposure and its carbonaceous components with adverse perinatal outcomes suggest that policies to reduce exposure would benefit public health., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: Human exposure to air pollution involves complex mixtures of multiple correlated air pollutants. To date, very few studies have assessed the combined effects of exposure to multiple air pollutants on breast cancer (BC) risk., Objectives: We aimed to assess the association between combined exposures to multiple air pollutants and breast cancer risk., Methods: The study was based on a case-control study nested within the French E3N cohort (5222 incident BC cases/5222 matched controls). For each woman, the average of the mean annual exposure to eight pollutants (benzo(a)oyrene, cadmium, dioxins, polychlorinated biphenyls (PCB153), nitrogen dioxide (NO 2 ), ozone, particulate matter and fine particles (PMs)) was estimated from cohort inclusion in 1990 to the index date. We used the Bayesian Profile Regression (BPR) model, which groups individuals according to their exposure and risk levels, and assigns a risk to each cluster identified. The model was adjusted on a combination of matching variables and confounders to better consider the design of the nested case-control study. Odds ratios (OR) and their 95 % credible intervals (CrI) were estimated., Results: Among the 21 clusters identified, the cluster characterised by low exposures to all pollutants, except ozone, was taken as reference. A consistent increase in BC risk compared to the reference cluster was observed for 3 clusters: cluster 9 (OR=1.61; CrI=1.13,2.26), cluster 16 (OR=1.59; CrI=1.10,2.30) and cluster 15 (OR=1.38; CrI=1.00,1.88) characterised by high levels of NO 2 , PMs and PCB153. The other clusters showed no consistent association with BC., Discussion: This is the first study assessing the effect of exposure to a mixture of eight air pollutants on BC risk, using the BPR approach. Overall, results showed evidence of a positive joint effect of exposure to high levels to most pollutants, particularly high for NO 2 , PMs and PCB153, on the risk of BC., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: This study examines longitudinal associations of air pollution and green space with cardiometabolic risk among children in the Netherlands., Methods: Three Dutch prospective cohorts with a total of 13,822 participants aged 5 to 17 years were included: (1) the Amsterdam Born Children and their Development (ABCD) study from Amsterdam (n = 2,547), (2) the Generation R study from Rotterdam (n = 5,431), and (3) the Lifelines study from northern Netherlands (n = 5,844). Air pollution (PM 2.5 , PM 10 , NO 2 , and elemental carbon (EC)) and green space exposures (density in multiple Euclidean buffer sizes) from 2006 to 2017 at home address level were used. Cardiometabolic risk factor clustering was assessed by a MetScore, which was derived from a confirmatory factor analysis of six cardiometabolic risk factors to assess the overall risk. Linear regression models with change in Metscore as the dependent variable, adjusted for multiple confounders, were conducted for each cohort separately. Meta-analyses were used to pool cohort-specific estimates., Results: Exposure to higher levels of NO 2 and EC was significantly associated with increases in MetScore in Lifelines (per SD higher exposure: β NO2  = 0.006, 95 % CI = 0.001 to 0.010; β EC  = 0.008, 95 % CI = 0.002 to 0.014). In the other two cohort studies, these associations were in the same direction but these were not significant. Higher green space density in 500-meter buffer zones around participants' residential addresses was not significantly associated with decreases of MetScore in all three cohorts. Higher green space density in 2000-meter buffer zones was significantly associated with decreases of MetScore in ABCD and Lifelines (per SD higher green space density: β ABCD  = -0.008, 95 % CI = -0.013 to -0.003; β Lifelines  = -0.002, 95 % CI = -0.003 to -0.00003). The pooled estimates were β NO2  = 0.003 (95 % CI = -0.001 to 0.006) for NO 2 , β EC  = 0.003 (95 % CI = -0.001, 0.007) for EC, and β 500m buffer  = -0.0014 (95 % CI = -0.0026 to -0.0001) for green space., Conclusions: More green space exposure at residence was associated with decreased cardiometabolic risk in children. Exposure to more NO 2 and EC was also associated with increased cardiometabolic risk., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Erik J. Timmermans reports financial support was provided by NWO Gravitation Grant (Exposome-NL, 024.004.017). Mingwei Liu reports financial support was provided by China Scholarships Council. Ilonca Vaartjes reports financial support was provided by NWO Gravitation Grant (Exposome-NL, 024.004.017). Gerard Hoek reports financial support was provided by NWO Gravitation Grant (Exposome-NL, 024.004.017). Diederick E. Grobbee reports financial support was provided by NWO Gravitation Grant (Exposome-NL, 024.004.017). Susana Santos reports financial support was provided by Marie Sklodowska-Curie Postdoctoral Fellowship Grant Agreement No. 101109136 (URBANE). Vincent W.V. Jaddoe reports financial support was provided by European Research Council (ERC Consolidator Grant, ERC-2014-CoG-648916). If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: Emerging evidence shows that long-term exposure to air pollution, road traffic noise, and greenness can each be associated with cardiovascular disease, but only few studies combined these exposures. In this study, we assessed associations of multiple environmental exposures and incidence of myocardial infarction using annual time-varying predictors., Materials and Methods: In a population-based cohort of 20,407 women in Sweden, we estimated a five-year moving average of residential exposure to air pollution (PM 2.5 , PM 10 and NO 2 ), road traffic noise (L den ), and greenness (normalized difference vegetation index, NDVI in 500 m buffers), from 1998 to 2017 based on annually varying exposures and address history. We used adjusted time-varying Cox proportional hazards regressions to estimate hazard ratios (HR) and 95 % confidence intervals (95 % CI) of myocardial infarction per interquartile range (IQR). Furthermore, we investigated interactions between the exposures and explored potential vulnerable subgroups., Results: In multi-exposure models, long-term exposure to greenness was inversely associated with incidence of myocardial infarction (HR 0.89; 95 % CI 0.80, 0.99 per IQR NDVI increase). Stronger associations were observed in some subgroups, e.g. among women with low attained education and in overweight (BMI ≥ 25 kg/m 2 ) compared to their counterparts. For air pollution, we observed a tendency of an increased risk of myocardial infarction in relation to PM 2.5 (HR 1.07; 95 % CI 0.93, 1.23) and the association appeared stronger in women with low attained education (HR 1.30; 95 % CI 1.06, 1.58). No associations were observed for PM 10 , NO 2 or road traffic noise. Furthermore, there were no clear interaction patterns between the exposures., Conclusion: Over a 20-year follow-up period, in multi-exposure models, we found an inverse association between residential greenness and risk of myocardial infarction among women. Furthermore, we observed an increased risk of myocardial infarction in relation to PM 2.5 among women with low attained education. Road traffic noise was not associated with myocardial infarction., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Although most source apportionments of VOCs use mixing ratios, about 23 % of published studies use mass concentrations. Thus, systematically exploring the changes in VOC source apportioned results caused by metric differences is important to assess the differences in key precursor apportionment results given the observed increases in O 3 pollution situation. Different monitoring instruments measured hourly VOC volumetric concentrations in three typical Chinese cities (i.e., Qingdao, Shijiazhuang, and Zhumadian). Converting volumetric to mass concentrations under standard and/or actual temperature-pressure conditions, VOC values with different metrics were obtained. The impacts of different metrics on the source apportionments were then investigated. Compared to the positive matrix factorization of the volumetric data (VC-PMF), the VOC species concentrations with low relative molecular mass (RMM) in the factor profiles substantially decreased in mass data analyses (MC-PMF). However, those species with high RMM substantially increased. There were no substantial differences in the apportioned source contributions based on standard and actual condition mass concentrations. However, the high-low rankings of percent contributions apportioned using the volumetric and mass data produced substantial differences. Compared with the VC-PMF results, the percent contributions of sources dominated by species with low RMM (e.g., natural gas usage and mixed sources containing natural gas usage) apportioned by MC-PMF decreased, while those of sources that emitted high RMM species (e.g., solvent usage and mixed sources containing solvent usage) increased. Source apportionments based on the volumetric concentration data had more practical significance compared to the mass concentration data results for control strategy development since the mass data analyses created issues., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: Long-term exposure to road traffic noise is associated with cardiovascular disease, but the evidence on respiratory diseases is just emerging. We aimed to examine the association between long-term exposure to road traffic noise and the incidence of acute lower respiratory infections (ALRIs) in adults., Methods: We followed 23,141 female nurses (age ≥ 44 years) from the Danish Nurse Cohort from baseline (1993 or 1999) to their first hospital contact (inpatient, outpatient, or emergency room) for ALRI, death, emigration or the end of 2015. The residential annual mean levels of road traffic noise (L den ) during the follow-up were estimated using the Nord2000 model. We applied time-varying Cox models to estimate the association of 3-year mean exposure to L den with ALRIs incidence and piecewise analysis to estimate the threshold of L den . We examined the robustness of the results by adjusting for residential exposure to air pollution, and the effect modification by attained age, socioeconomic status (SES), comorbidity, and lifestyle., Results: During 18.5 years of follow-up, 2,004 nurses developed ALRIs. In a linear model, we detected a statistically significant positive association between L den and ALRI, with a hazard ratio (HR) of 1.11 (95 % confidence interval (CI): 1.04, 1.17) per 9.2 dB (interquartile range, IQR). We observed non-linear association with a threshold at 57 dB, above which the HR was 1.25 (95 % CI: 1.09, 1.43) per IQR. Further adjustment for PM 2.5 reduced the HRs slightly to 1.21 (95 % CI: 1.04, 1.40). The associations were stronger for nurses with asthma, and in those with lowest SES., Conclusion: We present novel findings in support of the association between long-term exposure to road traffic noise and ALRIs, independent of air pollution, suggesting noise as a risk factor for infectious respiratory diseases., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Electricity production is a significant source of air pollution. Various factors, including electricity demand, generation efficiency, energy mix, and end-of-pipe control measures, are responsible for the emission changes during electricity generation. Although electricity production more than doubled from 1990 to 2017, air pollutant emissions showed a moderate increase or decrease, which was attributed to mitigating drivers such as increased clean energy use, improved power generation efficiency, and widespread installation of end-of-pipe control facilities. The absence of these mitigating drivers would have increased CO 2 , fine particulate matter (PM 2.5 ), black carbon, SO 2 , and NOx emissions in 2017 by 165 %, 403 %, 1070 %, 614 %, and 274 % than their actual levels, respectively. The improved electricity generation efficiency reduced potential CO 2 , PM 2.5 , SO 2 , and NOx emissions by 30 %, 295 %, 119 %, and 52 % compared to actual emissions, respectively. Meanwhile, the installation of end-of-pipe facilities reduced potential SO 2 and PM 2.5 emissions by 34.7 and 4.0 Tg, respectively. Considerable differences in emissions among countries were found to be attributable to their differences in electricity demand and the implementation of local mitigating polices., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Objective: Dementia is an important disease burden among the elderly, and its occurrence may be profoundly affected by environmental factors. Evidence of the relationship between air pollution and dementia is emerging, but the extent to which this can be offset by lifestyle factors remains ambiguous., Methods: This study comprised 155,828 elder adults aged 60 years and above in the UK Biobank who were dementia-free at baseline. Cox proportional hazard models were conducted to examine the associations of annual average levels of air pollutants in 2010, including nitrogen dioxide (NO 2 ), nitrogen oxides (NO X ), particulate matter (PM 2.5 , PM 10 , and PM coarse ) and lifestyle factors recorded at baseline [physical activity (PA), sleep patterns, or smoking status] with incident risk of dementia, and their interactions on both multiplicative and additive scales., Results: During a 12-year period of follow-up, 4,389 incidents of all-cause dementia were identified. For each standarddeviationincrease in ambient NO 2 , NO X or PM 2.5 , all-cause dementia risk increases by 1.07-fold [hazard ratio (HR) and 95 % confidence interval (CI) = 1.07 (1.04, 1.10)], 1.05-fold (95 % CI: 1.02, 1.08) and 1.07-fold (95 % CI: 1.04, 1.10), whereas low levels of PA, poor sleep patterns, and smoking are associated with an elevated risk of dementia [HR (95 % CI) = 1.17 (1.09, 1.26), 1.13 (1.00, 1.27), and 1.14 (1.07, 1.21), respectively]. Furthermore, these air pollutants show joint effects with low PA, poor sleep patterns, and smoking on the onset of dementia. The moderate to high levels of PA could significantly or marginally significantly modify the associations between NO 2 , NO X or PM 2.5 (P-int = 0.067, 0.036, and 0.067, respectively) and Alzheimer's disease (AD), but no significant modification effects are found for sleep patterns or smoking status., Conclusion: The increased exposures of NO 2 , NO X , or PM 2.5 are associated with elevated risk of dementia among elderly UK Biobank population. These air pollutants take joint effects with low PA, poor sleep patterns, and smoking on the development of dementia. In addition, moderate to high levels of PA could attenuate the incident risk of AD caused by air pollution. Further prospective researches among other cohort populations are warranted to validate these findings., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)